Assessment of Parent Income and Education, Neighborhood Disadvantage, and Child Brain Structure
Authors: Divyangana Rakesh, Andrew Zalesky, Sarah Whittle
Journal: JAMA Network Open (2022)

<h3>Importance</h3> Although different aspects of socioeconomic status (SES) may represent distinct risk factors for poor mental health in children, knowledge of their differential and synergistic associations with the brain is limited. <h3>Objective</h3> To examine the independent associations between distinct SES factors and child brain structure. <h3>Design, Setting, and Participants</h3> We used baseline data from participants aged 9 to 10 years in the Adolescent Brain Cognitive Development (ABCD) study. These data were collected from 21 US sites between September 2017 and August 2018. Study participants were recruited from schools to create a participant sample that closely reflects the US population. <h3>Exposures</h3> Neighborhood disadvantage was measured using the area deprivation index. We also used data on total parent or caregiver educational attainment (in years) and household income-to-needs ratio. <h3>Main Outcomes and Measures</h3> T1-weighted magnetic resonance imaging was used to assess measures of cortical thickness, surface area, and subcortical volume. <h3>Results</h3> Data from 8862 ABCD participants aged 9 to 10 years were analyzed. The mean (SD) age was 119.1 (7.5) months; there were 4243 girls (47.9%) and 4619 boys (52.1%). Data on race or ethnicity were available for 8857 of 8862 participants: 173 (2.0%) were Asian, 1099 (12.4%) were Black or African American, 1688 (19.1%) were Hispanic, 4967 (56.1%) were White, and 930 (10.5%) reported multiple races or ethnicities. Using 10-fold, within-sample split-half replication, we found that neighborhood disadvantage was associated with lower cortical thickness in the following brain regions (η<sup>2</sup> = 0.004-0.009): cuneus (<i>B</i>[SE] = −0.099 [0.013];<i>P</i> &lt; .001), lateral occipital (<i>B</i> [SE] = −0.088 [0.011];<i>P</i> &lt; .001), lateral orbitofrontal (<i>B</i>[SE] = −0.072 [0.012];<i>P</i> &lt; .001), lingual (<i>B</i>[SE] = −0.104 [0.012];<i>P</i> &lt; .001), paracentral (<i>B</i>[SE] = −0.086 [0.012];<i>P</i> &lt; .001), pericalcarine (<i>B</i> [SE] = −0.077 [0.012];<i>P</i> &lt; .001), postcentral (<i>B</i> [SE] = −0.069 [0.012];<i>P</i> &lt; .001), precentral (<i>B</i> [SE] = −0.059 [0.011];<i>P</i> &lt; .001), rostral middle frontal (<i>B</i> [SE] = −0.076 [0.011];<i>P</i> &lt; .001), and superior parietal (<i>B</i> [SE] = −0.060 [0.011];<i>P</i> &lt; .001). Exploratory analyses showed that the associations of low educational attainment or neighborhood disadvantage and low cortical thickness were attenuated in the presence of a high income-to-needs ratio (η<sup>2</sup> = 0.003-0.007). <h3>Conclusions and Relevance</h3> The findings of this cross-sectional study suggest that different SES indicators have distinct associations with children’s brain structure. A high income-to-needs ratio may play a protective role in the context of neighborhood disadvantage and low parent or caregiver educational attainment. This study highlights the importance of considering the joint associations of different SES indicators in future work.